Abstract
Multifidelity design optimization is a strategy that can reduce the high computational cost in cases where the high-fidelity model is too expensive to use directly in optimization. However, current multifidelity approaches cannot handle the high-dimensional problems commonly encountered in industrial settings. Furthermore, they cannot accommodate arbitrary analysis fidelities, directly handle multidisciplinary problems, or provably converge to the high-fidelity optimum. In this paper, we present a practical multifidelity approach that leverages the advantages of conventional gradient-based approaches. Rather than constructing a multifidelity surrogate, we perform a sequence of single-fidelity gradient-based optimizations. The framework determines the appropriate fidelity and updates it during the optimization process. Finally, we demonstrate the proposed approach on a multipoint aerostructural wing optimization problem with over a hundred design variables. The multifidelity approach reduces the computational cost by 59% compared to the high-fidelity approach while obtaining the same numerical optimum.
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Acknowledgements
This work was supported by Airbus in the frame of the Airbus–Michigan Center for Aero-Servo-Elasticity of Very Flexible Aircraft. Special thanks to Anne Gazaix, Tom Gibson, and Joel Brezillon for their expert advice and review of this paper. Additionally, the authors would like to thank Philip Gill and Elizabeth Wong for their assistance and insightful discussions regarding SNOPT. This research was partly supported through computational resources and services provided by Advanced Research Computing at the University of Michigan, Ann Arbor.
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The optimization uses MACH, of which several modules are available on GitHub under open source licenses. However, the multifidelity code is not yet available due to IP restrictions.
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Wu, N., Mader, C.A. & Martins, J.R.R.A. A Gradient-based Sequential Multifidelity Approach to Multidisciplinary Design Optimization. Struct Multidisc Optim 65, 131 (2022). https://doi.org/10.1007/s00158-022-03204-1
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DOI: https://doi.org/10.1007/s00158-022-03204-1